Data Engineering | NetrAInsights

What You'll Learn

Master modern data engineering tools and practices used in production systems. You'll build real data pipelines, design scalable architectures, and learn orchestration frameworks essential for AI/ML operations.

Data Pipelines: ETL/ELT design patterns, incremental loading, error handling
Apache Spark: Distributed computing, DataFrames, SQL on Spark
Orchestration: Apache Airflow, dbt for data transformation
Data Warehousing: BigQuery, Snowflake, schema design
Cloud Data Lakes: AWS S3, Google Cloud Storage, Delta Lake
Data Quality: Validation, monitoring, testing frameworks

Course Modules

📋 Week 1: Data Pipeline Fundamentals ▼

Data pipeline architecture patterns
ETL vs ELT trade-offs
Batch vs Stream processing
Error handling & retry logic
Lab 1: Build your first ETL pipeline with Python
Lab 2: Implement error handling & monitoring
Lab 3: Design incremental load strategy

⚡ Week 2: Spark & Distributed Processing ▼

Spark architecture & RDDs
DataFrames & SQL API
Partitioning & shuffling
Performance tuning & caching
Spark Streaming basics
Lab 4: Process 100GB dataset with Spark
Lab 5: Optimize slow Spark queries
Lab 6: Build real-time data ingestion
Lab 7: Implement data quality checks

🎼 Week 3: Orchestration & Cloud Data Platforms ▼

Apache Airflow DAGs & operators
dbt for data transformation
BigQuery & Snowflake essentials
Data lake design (Delta Lake, Iceberg)
Cloud cost optimization
Lab 8: Create complex Airflow DAG
Lab 9: Transform data with dbt
Lab 10: Design data warehouse schema
Lab 11: Deploy pipeline to cloud
Lab 12: Implement monitoring & alerting
Lab 13 (Capstone): End-to-end production pipeline

Prerequisites

Python programming (functions, classes, file I/O)
SQL fundamentals (SELECT, JOIN, GROUP BY)
Familiarity with command line / terminal
Basic understanding of distributed systems

Who Should Take This?

Data Analysts looking to move into engineering
Software Engineers building data systems
ML Engineers needing data pipeline expertise
Startups & Companies scaling data infrastructure

Tools & Tech Stack

Python 3.9+, Pandas, PySpark
Apache Airflow (orchestration)
dbt (data transformation)
PostgreSQL, BigQuery
Docker, Git, VS Code

Ready to Start?

Join hundreds of engineers building the data infrastructure of modern AI systems.

📧 Enroll Now

🗄️ Data Engineering

Level

Duration